Method and system for indoor RF mapping

ABSTRACT

A method is disclosed for determining a region of highest probability. At a first electronic device an RF signal is received comprising a first wireless signal and a second wireless signal is received. The first wireless signal and the second wireless signal are each other than solely a GPS signal. Based on both the first wireless signal and the second wireless signal, a region of highest probability is determined comprising an area of location estimates for the electronic device, the determined region of highest probability other than a region of highest probability determinable independently with each of the first RF signal and the second RF signal.

CROSS REFERENCES TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 61/479,390, filed Apr. 26, 2011, and incorporates thedisclosure of the application by reference.

FIELD OF THE INVENTION

The invention relates generally to location analysis and moreparticularly to RF based position determination.

BACKGROUND

The ability to locate RF devices within a building has long been soughtafter. Attempts to locate laptops, for example, and tagged devices havebeen proposed wherein a plurality of wireless receivers each transmit asignal and then try to identify through triangulation, for example, alocation of the RF signal source. In one such system, phased arrayantennas used for each of the wireless receivers allow them to determineangle of incidence of the RF signals. With two receivers, an accurateestimation of transmitter location is possible in a test environment.Unfortunately, in real world environments reflections and other signaldistortions result in errors in the location determinations and as such,these systems are problematic in commercial applications.

More recently, RF fingerprinting has been studied wherein a receiver isin motion and transmitted signals received thereby are used to estimatelocation. It has been found that with one transmitter in a controlledenvironment, it is possible to accurately estimate location.Unfortunately, like the other prior art, real world applications haveeluded this technology for many reasons. First, there is signalreliability issues where noise levels, reflections, interference,weather, speed, receiver battery levels, etc. all affect the results.Second, in highly controlled environments it is easier to assureuniqueness of a received RF signal at every point within the controlledspace. Third, controlled environments are highly static whereas thecommercial world is not. Fourth, in a controlled environment certainfeatures are excluded as problematic whereas in a commercialapplication, someone does not want to hear that they need to replace allof their metal fixtures with plastic ones.

It would be advantageous to provide a method and system for supportingcommercial indoor RF based location services.

SUMMARY OF EMBODIMENTS OF THE INVENTION

In accordance with an embodiment of the invention there is provided amethod comprising: a. receiving at a first electronic device an RFsignal comprising a first wireless signal and a second wireless signal,the first wireless signal and the second wireless signal other thansolely a GPS signal; and b. based on both the first wireless signal andthe second wireless signal, determining a region of highest probabilitycomprising an area of location estimates for the electronic device, thedetermined region of highest probability other than a region of highestprobability determinable independently with each of the first RF signaland the second RF signal.

In accordance with another embodiment of the invention there is provideda method comprising: a. receiving at a first electronic device an RFsignal comprising a wireless signal according to a first standard and awireless signal according to a second standard, the first standard andthe second standard other than a GPS standard; b. determining a firstregion of highest probability estimate for an electronic device basedsolely on the RF signal and determining a second region of highestprobability estimate for the electronic device based solely on thewireless signal; and c. determining the third region of highestprobability of the electronic device based on the first region ofhighest probability and the second region of highest probability.

In accordance with another embodiment of the invention there is provideda method comprising: a. receiving at a first electronic device a firstwireless signal according to a first standard and receiving at the firstelectronic device a second wireless signal according to the firststandard at a different time temporally proximate to the first wirelesssignal; b. determining a first region of highest probability based onthe first RF signal and determining a second region of highestprobability based on the second wireless signal; and c. determining thethird region of highest probability of the electronic device based onthe first region of highest probability and the second region of highestprobability.

In accordance with another embodiment of the invention there is provideda method comprising: a. receiving at a first electronic device a firstwireless signal according to a first standard and receiving at the firstelectronic device a second wireless signal according to the firststandard at a different time temporally proximate to the first wirelesssignal; b. receiving at the first electronic device a second firstwireless signal according to a first standard and receiving at the firstelectronic device a seconds second wireless signal according to thefirst standard at a different time temporally proximate to the firstwireless signal and second wireless signal; c. determining a firstregion of highest probability based on the first RF signal and secondwireless signal and determining a second region of highest probabilitybased on the second first wireless signal and second second wirelesssignal; and d. determining the third region of highest probability ofthe electronic device based on the first region of highest probabilityand the second region of highest probability.

In accordance with another embodiment of the invention there is provideda method comprising: a. receiving at a first electronic device a firstwireless signal according to a first standard and receiving at the firstelectronic device a second wireless signal according to the firststandard at a different time temporally proximate to the first wirelesssignal; b. receiving at the first electronic device a second firstwireless signal according to a first standard and receiving at the firstelectronic device a second second wireless signal according to the firststandard at a different time temporally proximate to the first wirelesssignal and second wireless signal; c. determining a first region ofhighest probability based on the first RF signal, a second region ofhighest probability based on the second wireless signal, a second firstregion of highest probability based on the second first wireless signaland a second second wireless signal based on the second second wirelesssignal; and d. determining the third region of highest probability ofthe electronic device based on the first region of highest probability,the second region of highest probability, the second first region ofhighest probability, and the second second region of highestprobability.

In accordance with another embodiment of the invention there is provideda method comprising: a. receiving at a first electronic device a firstwireless signal according to a first standard and receiving at the firstelectronic device a second wireless signal according to the firststandard; b. determining a second measured time based on the differencebetween a second time associated with the second region of highestprobability and a third time associated with a third region of highestprobability; c. determining a velocity value; and d. determining a thirdregion of highest probability based on the first wireless signal, thesecond wireless signal, measured time, and the velocity value.

In accordance with another embodiment of the invention there is provideda method comprising: a. receiving at a first electronic device a firstwireless signal and a second wireless signal; b. determining using RFfingerprinting a first region of highest probability based on the firstwireless signal; c. determining using RF fingerprinting a second regionof highest probability based on the second wireless signal; and d.determining based on the first and second regions of highest probabilitya third region of highest probability for the electronic device.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a prior art RF Fingerprinting system in a controlledspace.

FIG. 2 illustrates a prior art RF Fingerprinting system in anuncontrolled space.

FIG. 3 illustrates a prior art RF Fingerprinting system in anuncontrolled space.

FIG. 4 is a block diagram of an RF data capturing system in anuncontrolled space.

FIG. 5 is a block diagram of an RF data capturing system in anuncontrolled space.

FIG. 6 is a flow diagram of a system for mapping locations based on RFsignal data.

FIG. 7 illustrates a flow diagram of processing data collected by asystem for mapping locations based on RF signal data.

FIG. 8 is a diagram for illustrating location estimation for a devicecomprising an RF signal receiver circuit.

FIG. 9 is a flow diagram of the process executed by the server toresolve errors from two independent wireless signal data sets toestimate a single location of a device.

FIG. 10 is a diagram for illustrating determining a location of a devicecomprising RF signal receiver circuits by the relation of RF signaldata, the associated location data, previous RF signal data and previouslocation data.

FIG. 11 illustrates a plurality of known devices collecting RFfingerprint data for a building to determine a location estimate for amobile device.

FIG. 12 illustrates RF fingerprint data and location data collectedsimultaneously in order to allow accurate and effective locationestimation based on data later provided from RF devices.

FIG. 13 illustrates a side view of a mapping platform for use in mappingof locations to form a database of locations and associated RFfingerprints therefore.

FIG. 14 illustrates a top view of an interior layout of a space.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

The following description is presented to enable a person skilled in theart to make and use the invention, and is provided in the context of aparticular application and its requirements. Various modifications tothe disclosed embodiments will be readily apparent to those skilled inthe art, and the general principles defined herein may be applied toother embodiments and applications without departing from the scope ofthe invention. Thus, the present invention is not intended to be limitedto the embodiments disclosed, but is to be accorded the widest scopeconsistent with the principles and features disclosed herein.

Referring to FIG. 1, shown is a simplified prior art RF fingerprintingsystem. A controlled space 100 is defined in which RF signals provide alevel of unique location identification. Controlled space 100 hassufficient reflectivity to support some small level of signal reflectionand multipath. At a corner of controlled space 100 is disposedtransmitter 101. Transmitter 101 is an RF signal transmitter accordingto a known protocol such as 802.11. At 102 are shown a plurality ofsignal paths for a signal transmitted and each reaching a samedestination point 103. As will be appreciated, a propagation time foreach of said signals 102 may differ and, as such, the data content ofthe signals reaching point 103 at an instance of time indicateinformation relating to propagation time and therefore relating to pathlength. Thus, when a transmitted RF signal transmitted from transmitter102 is of common signal strength, the RF signals received at each andevery location differ and can be used to identify each locationuniquely. Conversely, even when transmitter 102 transmits at differentsignal levels, it is possible to uniquely identify each location basedon a ratio of signal strength between different received signals.

Referring to FIG. 2, shown is a same RE fingerprinting system as that ofFIG. 1 wherein the space 200 is uncontrolled. Space 200 has sufficientreflectivity to support some small level of signal reflection andmultipath. At a corner of controlled space 200 is disposed transmitter201. Transmitter 201 is an RF signal transmitter according to a knownprotocol such as 802.11. At 202 a and 202 b are shown a plurality ofsignal paths for a signal transmitted and each reaching a destinationpoint 203 a and 203 b, respectively. Thus, when a transmitted RF signaltransmitted from transmitter 202 is of common signal strength, the RFsignals received at 203 a and at 203 b are same and cannot be used toidentify each location uniquely. The space is bisymmetrical and as such,each unique RF fingerprint is not unique and leads to two possiblelocation estimates.

Referring to FIG. 3, shown is another uncontrolled space 300.Uncontrolled space 300 is of unknown reflectivity. At a corner ofuncontrolled space 300 is disposed transmitter 301. Transmitter 301 isan RF signal transmitter according to a known protocol such as 802.11.At 302 shown are a plurality of signal paths for a signal transmittedand each reaching a same destination point 303. As will be appreciated,a propagation time for each of said signals 302 may differ and, as such,the data content of the signals reaching point 303 at an instance oftime indicate information relating to propagation time and thereforerelating to path length.

Here, fixtures 305 in the form of metal shelving units are disposedwithin the space and merchandise 306 is added to and removed from themetal-shelving units. Thus, an RF signal received on one day differssignificantly from an RF signal received on another day. Thus, the priorart RF fingerprinting methodology fails except in very specific andcontrolled situations. Further, though the system may lend itself toaccurate results at some points in time, identifying those results asaccurate is based on human operator control of the space 300 as opposedto the system itself.

Referring to FIG. 4, shown is a simplified block diagram of a system forcapturing RF data for characterizing an uncontrolled space. System 400is shown comprising a plurality of components including the following: alocation sensor in the form of dead reckoning system 401, an RF sensorin the form of WiFi antenna 402, a second RF sensor in the form ofBluetooth® antenna 403, a third RF sensor in the form of cellular datasignal sensor 404, a fourth RF sensor in the form of a 3G cellular datasignal sensor other similar function cellular data signal sensor 405, amemory circuit 406 and a processor 407. For example, memory circuit 406comprises a removable memory circuit such as a USB key. Alternatively,the memory circuit is replaced by a communication circuit forcommunicating the data from system 400 to a server for storage.Optionally, the system is implemented on a rolling cart to facilitatemoving of the system inside a space. Further optionally, system 400comprises GPS receiver 410 for indicating a geo-location when outside ofthe space.

Referring to FIG. 5, shown is a simplified block diagram of a system forcapturing RF data for characterizing an uncontrolled space. System 500is shown comprising a plurality of components including the following: alocation sensor in the form of dead reckoning system 501, an RF sensorin the form of WiFi antenna 502, a second RF sensor in the form ofBluetooth® antenna 503, a third RF sensor in the form of cellular signalsensor 504, a fourth RF sensor in the form of a 3G cellular data sensoror other similar function cellular data signal sensor 505, a memorycircuit 506 and a processor 507. For example, memory circuit 506comprises a removable memory circuit such as a USB key. Alternatively,the memory circuit is replaced by a communication circuit forcommunicating the data from the system 500 to a server for storage.Optionally, the system is implemented on a rolling cart to facilitatemoving of the system inside a space. Further optionally, the system 500comprises GPS receiver 510 for indicating a geo-location when outside ofthe space.

The system 500 further comprises a port for coupling with portablewireless communication devices in the form of cellular phones, smartphones, mobile tablets, and mobile modems 508. Of course, other wirelessdevices are also contemplated for use with the system 500. Thus forexample, the system 500 is implemented with an Android® smart phone, aniPhone®, a Blackberry® phone, a Windows® 7 phone, etc. each sensing RFsignals and providing the data to the system 500 for storage.

Referring to FIG. 6, shown is a simplified flow diagram of a system suchas that shown in FIG. 5 used for mapping of locations based on RF signaldata. The system is set up and powered for use at an outside location at600. The system provides an indication of GPS signal reception at 602.At this point, a reasonably accurate location is known for the system500. At 603, the system is wheeled into the space in the form of ashopping mall. The system is provided with a dead reckoning system 501and, as such, provides an indication from the dead reckoning system 501of actual motion and location of the system 500. At 604, the system ismoved through a path. The path is preferably selected to be short enoughto allow for relatively small dead reckoning system error while beinglong enough to maintain a level of efficiency in data gathering.Throughout the movement of 604, the system iteratively senses RE signalsand provides the signal data and the dead reckoning data for storage 605within memory circuit 506. Alternatively, the data is transmitted via awireless data communication signal to a server for storage thereby.Though the system is described with a collection of raw data from the RFreceivers, it is also possible to preprocess the data before storagethereof. That said, storage of more raw data is useful in improving andmaintaining of a data set so formed. The process continues until 606where the system is returned to a location where a GPS signal isreceived and a clear indication of location is thereby achieved.

Once a path is traversed, the process is repeated for numerous otherpaths within a same space. This allows for characterization of a spaceby capturing data relating to RF signals received at each of a pluralityof interior locations and storing the data in association with knownlocation data based on dead reckoning and/or GPS data. Thus, a samesystem is also usable to form an RF map of an outdoor space. Combiningthe data captured from the plurality of paths results in a map of theinterior space of the building and keeps the error introduced by thedead reckoning system to a minimum. Alternatively the system traversesthe building once to capture the data.

Once sufficient data is captured, then processing of the data tocharacterize the space is supported. Of course, processing could occurduring capture, after capture, or during use of the data depending onthe system requirements, performance, and other design criteria.Optionally, mapping the location based on RF signal data is repeatedwherein acquiring more RF data increases the amount of location data andtherefore presents further opportunity for resolving errors orprocessing of unknown RF fingerprint data to determine a location.

Once the raw data is uploaded from the dead reckoning system to theserver it is processed. Alternatively the data is transferred to theserver via the removable memory circuit comprising the raw data, forexample a USB key. Further alternatively, the data is preprocessed priorto being transferred to a database. The dead reckoning data and the GPSdata are made consistent. This involves evaluating an error vector forthe dead reckoning data and applying a corrective function to thelocation data within the raw data in order to result in correctedlocation data. When an error vector is very small, correction is otherthan applied. Of course, in an error vector determination, knownimprecision in GPS positioning is optionally taken into account.

Once the location data is corrected for each path traversed, the RFcommunication signals for each different RF signal source, Bluetooth®transmitter, WiFi transmitter, Cellular transmitter, 3G data signaltransmitter, 4G data signal transmitter, and other similar function datasignal transmitters are each characterized independently to determine RFfingerprints associated with each location, and to identify RFfingerprinting issues such as non-unique RF fingerprints and noisyenvironments. Thus, a resulting data set comprising a plurality of RFfingerprints for each of a plurality of locations results.

FIG. 7 illustrates a flow diagram of processing data collected by thedead reckoning system by the server. Once the raw data has been uploadedfrom the dead reckoning system, for example via a WiFi datacommunication network, the raw data is processed at 701. The serverevaluates an error vector for the dead reckoning system at 702. When theerror vector is sufficiently large but not too large, a correctivefunction is applied to the location data wherein the location data iscorrected for errors at 703. When the error vector is very small, acorrective function is other than applied to the location data.Typically, a very small error is one that is within a predeterminedtolerance for location errors for the system. When an error is verylarge, the data is preferably discarded and new data is captured in anattempt to acquire better source data. Optionally, an indication of datacollection error is provided. The RF signals from each signal source arecharacterized and an RF fingerprint is determined for each signal sourcecorrelated to a location in the path traversed 704. The RF fingerprints,associated locations, and error margins are stored in database memory at705.

According to an embodiment of the invention a location of a devicecomprising an RF signal receiver circuit is often determinable by therelationship of RF fingerprint data and the associated location data.FIG. 8 is a simplified diagram for illustrating location estimation forsuch a device. A person 801 carrying a smart phone 802 enters a building800 wherein RF fingerprint data and location data have been captured,for example using the method of FIG. 7. Grid 803 indicates locationswithin the building. The person 801 stops at the entrance 804. The smartphone 802 is in communication with a server 805 via a Local Area Network(LAN). The server 805 comprises a dataset including corrected locationdata and RF fingerprints relating to an interior of the building, andprovides location information to the smart phone 802 in response to RFsignal data. The smart phone 802 comprises a WiFi communication circuitand a 3G data communication circuit for receiving RF signals 806 andcollects RF signal data for the WiFi communication signal and 3G datacommunication signals. The smart phone 802 provides data relating to theWiFi communication signal and the 3G data communication signal to server805. In conjunction with the location data and RF fingerprints for thebuilding 800 the server 805 determines a first location estimaterelating to the WiFi communication signal data at coordinates (1,1). Theserver 805 processes the 3G data communication signal data inconjunction with the location data and RF fingerprints of the building800 and determines a second location estimate at coordinates (1,1). Thelocation determined based on the independent RF signals, WiFicommunication signals and 3G data communication signals, indicate thesame coordinates confirming that (1,1) is likely a location of person801. The person 801 notes the location (1,1). As the person proceedswalking through the building 800 the server continuously receives WiFicommunication signal data and 3G data communication signal data from thesmart phone 802 and determines the smart phone's the most likelylocation along the path traversed. As the building 800 is large anddifficult to navigate, when is it is time to leave the building theperson 801 refers to the smart phone 802 to determine the presentlocation in order to navigate to the entrance at coordinates (1,1).

At the person's present position the server 805 receives the WiFicommunication signal data and 3G data communication signal data fromsmart phone 802 to determine the smart phone's most likely location. Inconjunction with the location data and RF fingerprint data for thebuilding 800, the server 805 determines a first location estimaterelating to the WiFi communication signal data, for example atcoordinates (5,8) as shown. The server 805 processes the 3G datacommunication signal data in conjunction with the location data and RFfingerprint data for the building 800 and determines a second locationestimate, for example at coordinates (4,7). The data provided by theWiFi communication signal and the 3G data communication signal providetwo different location estimates indicating at least one result isincorrect. The results are optionally stored in server memory. Theserver 805 continues to receive new WiFi communication signal data fromthe smart phone 802. The server 805, processes the new WiFicommunication signal data with the previous WiFi communication signaldata, to resolve errors in location estimates based on the new WiFicommunication signal data and previous WiFi communication signal data,and updates the previous and new location estimate. This iterativeprocess of collecting and processing new data, resolving errors betweenthe new data and previous data, and updating a location estimate, isrepeated at predetermined intervals. Alternatively, the intervals aredetermined based on a convergence of the error. Further alternatively,the intervals are other than predetermined. Typically, this process isiterated until the resulting error is below a predetermined thresholderror. The server 805 continues to receive other new 3G datacommunication signal data from the smart phone 802. The server 805,processes the other new WiFi communication signal data with the previousnew 3G data communication signal data, to resolve errors in locationestimates based on the new 3 G communication signal data and previous 3G communication signal data, and updates the previous and new locationestimate. Thus, an iteration is completed and another iteration isoptionally commenced. During this process, signal data, associatedlocation data, and associated errors are stored in a dataset in servermemory. Once the errors are resolved for the WiFi communication signaldata and the 3G data communication signal data, the location estimatesfrom both sources are processed and a location estimate for the smartphone is determined, for example at coordinates (5,8) as shown.Optionally, the RF communication signals are Bluetooth®, 4G or latercellular data signals, other RF signals, and are other than a GPSsignal. Optionally the device is a cell phone, tablet, laptop, PDA, orother device comprising at least a receiver circuit for receiving RFsignals according to each of at least two standards. Typically, this isachieved using at least two RF signal receiver circuits.

Alternatively, the determined location estimate based on the WiFicommunication signal data and associated location data is (3,3) and thelocation estimate based on the RF communication signal data andassociated location data is (4,7). The WiFi communication signal dataand the 3G data communication signal data do not correlate to the samelocation. The iterative process of collecting and processing new WiFicommunication signal data, to resolve errors between the new WiFicommunication signal data and previous WiFi communication signal data,does not result in an error below a predetermined threshold error. Theiterative process of collecting and processing new 3G data communicationsignal data, to resolve errors between the new 3G data communicationsignal data and previous 3G data communication signal data, also doesnot result in an error below a predetermined threshold error. A locationestimate relating to each independent source is not reliable; hence RFsignal data from both sources are used to determine a location estimate.An iterative process is used to resolve the errors in each signal in acompatible fashion such that determining a location estimate results inan approximately compatible error for both estimations. For example,using an analytic process it can be determined that certain forms oferror inducing events induce different but predictable errors indifferent signals. More particularly, for example, a metal panelpredictably attenuates signals propagating therethrough and reflectssignals propagating thereto. As such a metal plate placed between thedevice location and a transmitter but not between the device locationand another transmitter and also disposed close to the device location,will induce predictable error in each location estimate that isresolvable in a compatible fashion once a cause of the error is selectedas a metal object or plate. Further, when data is captured at differenttimes within a limited timeframe, the inter-relation between adjacentlocations and the errors and compatible causes of the error, furtherallows for error resolution. Optionally, the RF communication signalsare Bluetooth® signals, 4G or later cellular data signals, other RFsignals, and are other than a GPS signal. Optionally the device is acell phone, smart phone, tablet, laptop, or other device comprising atleast a receiver circuit for receiving RF signals according to each ofat least two standards. Typically, this is achieved using at least twoRF signal receiver circuits.

FIG. 9 is a flow diagram of the process executed by a server to resolveerrors from two independent RF signal data sets to estimate a singlelocation of a device, for example a device comprising at least areceiver circuit for receiving RF signals according to each of at leasttwo standards. The two independent RF signal data sets are in the formof a WiFi communication signal data and 3G data communication data froma device in the form of a smart phone comprising a WiFi communicationcircuit and a 3G data communication circuit. The server receives WiFicommunication signal data from the smart phone and determines a locationestimate based on the WiFi communication signal data at 901. The serverdetermines an error value for the location estimate based on otherlocation estimates determined temporally proximate the locationestimate. At 902, it is determined if error is below a predeterminederror threshold or if the location estimate is valid—lies within auseful range of location estimates. If it is determined that the erroris not below a predetermined error threshold and that the locationestimate is valid, the WiFi communication signal data, associatedlocation data, and error data are stored in a data set in memory at 903and step 901 is iterated and, using the previous WiFi communicationsignal data and associated location data, as well as new WiFicommunication signal data and associated location data the serverupdates the previous and new location estimate. At 902 the server againdetermines if the error is below a predetermined error threshold or ifthe location estimate is valid. Optionally when the data is invalid, theinvalid location estimate and associated location information are storedin a second data set, 904, and the process returns to 901. At 901 theserver continues to iterate gathering data and updating the locationestimate until the error is below a predetermined error threshold.Clearly, when the smart phone is moving, the updating of locationestimates involves updating of location estimates for a moving objectbased on known potential paths of motion and, as such, is not updating asame location each iteration, but instead trying to update a locationbased on a determined and feasible path of motion.

At step 905 the server receives 3G data communication signal data fromthe smart phone and determines a location estimate based on the data atstep 906. At 906, it is determined if error is below a predeterminederror threshold or if the location estimate is valid—lies within auseful range of location estimates. If it is determined that the erroris not below a predetermined error threshold and that the locationestimate is valid, the 3G data communication signal data, associatedlocation data, and error data are stored in a data set in memory at 907and step 905 is iterated and, using the previous 3G data communicationsignal data and associated location data, as well as new 3G datacommunication signal data and associated location data the serverupdates the previous and new location estimate. At 906 the server againdetermines if the error is below a predetermined error threshold or ifthe location estimate is valid. Optionally when the data is invalid, theinvalid location estimate and associated location information are storedin a second data set, 908, and the process returns to 905. At 905 theserver continues to iterate gathering data and updating the locationestimate until the error is below a predetermined error threshold.Clearly, when the smart phone is moving, the updating of locationestimates involves updating of location estimates for a moving objectbased on known potential paths of motion and, as such, is not updating asame location each iteration, but instead trying to update a locationbased on a determined and feasible path of motion. At 909 the serverdetermines the most likely location of the smart phone. The RFfingerprint data and associated errors are stored in memory at step 910.Optionally, the RF communication signals are Bluetooth® signals, 4G orlater cellular data signals, other RF signals, and are other than a GPSsignal. Optionally the device is a cell phone, smart phone, tablet,laptop, PDA, or other device comprising at least a receiver circuit forreceiving RF signals according to each of at least two standards.Typically, this is achieved using at least two RF signal receivercircuits.

According to an embodiment of the invention a location of a devicecomprising RF signal receiver circuit is often determinable by therelation of RF signal data, the associated location data, previous RFsignal data and previous location data. Referring to FIG. 10, a user1001 with a device comprising receiver circuit for receiving RF signalsaccording to each of at least two standards, such as a smart phone 1002,for receiving RF signals in the form of Bluetooth® communication signalsand WiFi communication signals enters building 1004 wherein locationdata and RF Fingerprint data has been collected and is stored in memoryof server 1003. Utilizing the Bluetooth® communication signal data andthe WiFi communication signal data the server 1003 estimates the user'slocation at A (3,3) 1005. The signal data from both sources and theassociated location data are stored in a data set in the server'smemory. The user moves from location A 1005 to location B 1006. At apreselected interval of time, for example 1 second, the server againgathers data from both signal sources and attempts to determine anestimate for location B. In that one second the user does not move agreat distance from location A. In fact the server defines a region ofspace in which the user is most likely to be located. This region ofhighest probability (RHP) from location A is shown in FIG. 10 as 1007.The location estimate relating to the Bluetooth® signal data is (7,9)and location estimate relating to the WiFi communication signal data is(4,3). The location (7,9) is out of the RHP from location A 1007 and istherefore most likely incorrect; hence the Bluetooth® signal data ismost likely in error. RHP evaluation and comparison aids in providing amore accurate location estimate of the location of the smart phone 1002as the Bluetooth® signal data does not heavily influence the finallocation determination process. The server includes the RHP fromlocation A 1007 and resolves the error, determining an estimate forlocation B 1008 at (4,4). The Bluetooth® and WiFi signal data, RHP fromlocation A and location data are stored in a dataset in server memory.Also shown in FIG. 10 are the RHPs from location B 1009 and location C1010. This process is repeated through out a path traversed by the user.Using RHP analysis allows for resolution of paths traversed even whenmultiple errors are present since a given wireless data set oftenresolves to few or one possible solution. Optionally, the RFcommunication signals are WiFi signals, 3G cellular data signals, 4G orlater cellular data signals, other RF signals, and are other than a GPSsignal. Optionally the device is a cell phone, tablet, laptop, PDA, orother device comprising at least a receiver circuit for receiving RFsignals according to each of at least two standards. Typically, this isachieved using at least two RF signal receiver circuits.

According to an embodiment of the invention, a disturbance influencingall RF signals is detected whereby a common error is determinable andcorrectable. For example, a user with an iPad® is walking through abuilding wherein an RF fingerprint data and location data have beenpreviously captured. The server continuously updates and transmitslocation estimates to the iPad. A large metal container has been movedinto the building after collection of the RF fingerprint data andlocation data and therefore the server does not have updated RFfingerprint data for the location, most notably near the metalcontainer. When the user walks close to the metal container the RFsignals received by the iPad likely correlate poorly with the previouslycaptured data. The server comprises behavior models that model theeffect of known objects on a set of RF signals. Based on the nature ofthe RF signal data from each source, the server predicts which object ismost likely causing interference with all RF signals and applies acompensation function to minimize the effects when determining alocation estimate. Optionally, the RF communication signals areBluetooth® signals, WiFi signals, 3G cellular data signals, 4G or latercellular data signals, other RE signals, and are other than a GPSsignal. Optionally the device is a cell phone, tablet, laptop, PDA, orother device comprising at least a receiver circuit for receiving RFsignals according to each of at least two standards. Typically, this isachieved using at least two RF signal receiver circuits. Alternativelythe object comprises plastics, organic materials, including humans,liquids, man made materials, and naturally existing materials.

According to an embodiment of the invention a disturbance influencing atleast one RF signal is detected and a differential error is determinedand corrected. For example, a user with a mobile tablet in the form ofan iPad® is walking through a building wherein RF fingerprint data andlocation data have been captured. The server continuously updates andtransmits location estimates to the iPad®. A large wooden container hasbeen moved into the building after collection of the RF fingerprint dataand location data by the system, therefore the server does not have RFfingerprint data for the location, most notably near the woodencontainer. When the user walks close to the wooden container at leastone of the RF signals received by the iPad®, for example the Bluetooth®signal, are uncorrelated with the RF fingerprint data previouslycollected and stored. The server comprises behavior models that modelthe effect of known objects on RF signals. Based on each of RF signalsthe server predicts which object is most likely causing noteddiscrepancies and applies a compensation function to minimize theeffects for determining a location estimate. For example the serverprocesses each of the signal data and predicts that wood is affecting abehavior of the Bluetooth® signal. Applying a compensation function tothe Bluetooth® signal data the effect of the wood is reduced therebyrendering the Bluetooth® signal data functionally useful for determiningthe estimated location of the iPad. Optionally, the RF communicationsignals are WiFi signals, 3G cellular data signals, 4G or later cellulardata signals, other RF signals, and are other than a GPS signal.Optionally the device is a cell phone, tablet, laptop, PDA, or otherdevice comprising at least a receiver circuit for receiving RF signalsaccording to each of at least two standards. Typically, this is achievedusing at least two RF signal receiver circuits. Alternatively the objectcomprises metals, plastics, organic materials, including humans,liquids, man made materials, and naturally existing materials.

According to an embodiment of the invention RF signals for eachdifferent RF signal source, Bluetooth® transmitter, WiFi transmitter,Cellular transmitter, 3G data signal transmitter, 4G data signaltransmitter, and other similar function data signal transmitters areeach characterized independently, by coupling said devices to the systemas described in FIG. 4, to determine RF fingerprint data associated witheach known device, associated location data, and to identify RFfingerprinting issues such as non-unique RF fingerprints and noisyenvironments. Thus, a resulting data set for each known devicecomprising a plurality of RF fingerprints for a plurality of locationsresults. Similar to the previously noted embodiment for differentialerror determination, each device potentially receives signalsdifferently and may impose error on the received signal data. Though theerror is also characterizable in use and a data set is determinable toreduce the error for a given device dynamically, there are advantages tocharacterizing the RF fingerprint data error for different devicesthrough data capture and RF fingerprint data collection.

Known devices include but are not limited to iPhone®, iPad®, Windows 7Smart Phones®, Android® smart phones, and Blackberry Smart Phones® aswell as iPods®, iPads®, mobile tablets, laptops, and PDAs. Theproperties of the RF signal communication circuitry for each knowndevice vary; therefore, generating a unique dataset of RF fingerprintsfor each device is beneficial. One of skill in the art easily sees theadvantage of employing the unique data sets when estimating a locationof a known device. For example, a person carrying an iPhone and walkinginto a building wherein iPhone RF fingerprint data and location data hasbeen captured is more easily located based on a data set captured with asame device—an iPhone®. The server communicates with the iPhone via aLAN, discovers that the device is an iPhone, and uses the RF fingerprintdata relating to iPhones® when estimating a location of the iPhone®. TheRF signal data transmitted from the iPhone to the server likely moreclosely resembles the data in the iPhone RF fingerprint dataset than RFfingerprints for another device. Resulting in more accurate locationestimations and less error to correct.

According to an embodiment of the invention a plurality of known devicesthat comprise RF signal communication receiver circuits collects RFFingerprint data for a building to determine a location estimate for amobile device comprising an RF signal receiver circuit disposed withinthe building. Similar to the system and method described in FIG. 5 andFIG. 6, a dead reckoning system traverses paths within the building forcollecting location data. However, the dead reckoning system does notreceive RF signals or transmit RF signal data to a server, but comprisesmobile devices comprising RF signal communication transmitter circuitsfor transmitting RF signals of different standards. As the deadreckoning system traverses paths within the building, known devicesdisposed within communication range of the building detect the RFsignals transmitted from the mobile devices and transmits correlating RFsignal data to a server with which they are in communication, forexample via a LAN. FIG. 11 illustrates a dead reckoning system 1101traversing a building, for example a shopping mall 1102. Coupled to deadreckoning system 1101 are mobile devices in the form of a smart phone1103 a, tablet 1103 b, and PDA 1103 c. In the mall interior are knowndevices in the form of WiFi switch 1104, WiFi switch 1105, and laptop1106, and are in communication with server 1107 via a LAN. Disposedoutside the mall is a known device in the form of a cell tower 1108 andis in communication with server 1107 via a cellular data communicationsystem. As the dead reckoning system traverses through the mall storesand corridors it transmits location data to server 1107. Simultaneously,WiFi switch 1104, WiFi switch 1105, and laptop 1106 detect RF signalstransmitted from the smart phone 1103 a, tablet 1103 b, and PDA 1103 cin the form of WiFi signals and transmits WiFi communication signal datato server 1107. Also, cell tower 1108 detects RF signals transmittedfrom the smart phone 1103 a and PDA 1103 c in the form of 3G datacellular signals and transmits 3G cellular data communication signaldata to server 1107. This method of collecting RF fingerprint data andassociated location data obviates the need for the smart phone 1103 a,tablet 1103 b, and PDA 1103 c to transmit any RF fingerprint data toserver 1107. Optionally, the RF communication signals are Bluetooth®signals, 3G cellular data signals, 4G or later cellular data signals,other RF signals, and typically other than a GPS signal. Optionally thedevice is a cell phone, tablet, laptop, PDA, or other device comprisingat least a receiver circuit for receiving RF signals according to eachof at least two standards. Typically, this is achieved using at leasttwo RF signal receiver circuits.

A person skilled in the art will see that acquiring RF fingerprint dataand associated location data as described in FIG. 11 lends itself to theembodiments described above.

Using a system such as that described in FIG. 4, a database of RFfingerprints and locations is formable. For example, the dead reckoningsystem is rolled through an indoor location as described hereinabove.Upon traversing a path, an error in dead reckoning is determined and isdistributed along the path according to any of a number of knownstatistical models. The locations are then stored along with theirassociated RF fingerprint data for each of a number of differentcommunication standards. When two paths overlap or cross, data iscollected for one or more locations more than once and a resolutionprocess is employed to resolve between the two different data sets.Preferably, the resolution process aids in correcting errors in one orboth datasets, for example in more accurately correcting dead reckoningsystem error. Alternatively, the resolution process involves morecomplex processes for trying to determine changes in the environmentbetween data collection times—for example, additional pedestriantraffic. Yet further alternatively, video data is captured with the RFfingerprint data and is used to resolve between different conflictingdata. The RF fingerprint data and location data, once assembled into asingle dataset, form a map. Locations between locations for which datahas been collected are determined or mapped based on analytical methodsfor determining RF signals in intervening locations for each of the RFsignal standards measured. By using an altimeter within thedata-gathering device, it is possible to account for errors resultingfrom movement up or down as are known to occur. For example, intraversing a ramp up and down, a dead reckoning system will determine adistance travelled but location only varies along the horizontaldirection—two vectors of the three in three-space. Thus, a greaterdistance may actually be travelled without an actual error havingoccurred in the dead reckoning system measurement. Clearly the data set,once collected, is augmentable at intervals or continuously to providemore accurate data and data relating to variations in a givenenvironment. For example, traversing a new path each night once ashopping mall is closed, allows the intervening space within the mall tobe mapped over time thereby reducing a distance between measured datapoints for use in analyzing intervening spaces for a given dataset.Advantageously, such a continuous data collection also allows foridentification and correction for updates and changes to the shoppingmall interior. Optionally, the dataset once collected is analyzed toallow for more efficient processing thereof. For example, RFfingerprints for intervening spaces are estimated, as are potentialsources of error. Further alternatively, similar RF fingerprints areidentified to allow for more effective distinction between locations forsaid similar RF fingerprints. In accordance with yet another embodimentof the invention there is provided a method and system for mapping ofinterior spaces for each of a plurality devices to build a database ofRF fingerprints that are device specific. Further, such a databaseallows for operation of the system with a multitude of unknown devicesby mapping each to a most closely related dataset and/or by developing atransform to transform collected RF fingerprint data to most closelyresemble a dataset. Of course, for each of a plurality of standards asingle device may be most closely associated with a different dataset—adifferent device. For example, a smart phone may closely resembleanother smart phone in cellular RF signal RF fingerprint whileresembling an iPod most closely in WiFi RF fingerprint data.

In accordance with an embodiment of the invention, RF fingerprint dataand location data are collected simultaneously in order to allowaccurate and effective location estimation based on data later providedfrom RF devices. Optionally, the data sets are collected from differentRF devices of a similar nature such as smart phones. A system asdescribed in FIG. 4 having known devices coupled thereto is used tocollect the data. Alternatively, another system is used for datacollection. A database is formed comprising data for mapping of one ormore building interior. As further data is collected the database andmap are optionally updated resulting in a “living database” that changesas the interior of the building is modified. Further, during use, thesystem, in determining errors and consistent changes, optionally updatesthe database dynamically to reflect a changing environment and toimprove performance and effectiveness for location determination.

Referring to FIG. 12, shown is a building in the form of a hardwarestore 1200, wherein RF fingerprint data and location data have beencaptured, for example using at least one of the methods describedhereinabove. Two metal shelves 1202 a and 1202 b are present at a timeRF fingerprint data is collected and is stored in a “living database” onserver 1206. A new metal shelf 1203 is subsequently placed on thehardware store floor and therefore RF fingerprint data relating to themetal shelf 1203 are other than stored in the “living database.” Person1204 walks into the hardware store 1200 carrying a device in the form ofa 3G cellular phone 1205 comprising RF signal communication circuitry.Upon entry into the hardware store 1200, the 3G cellular phone 1205 isin communication with server 1206 via a LAN to which it transmits REsignal data in the form of 3G data communication signal data and WiFisignal communication data each relating to fingerprints of signalsreceived by the 3G cellular phone 1205. The person 1204 walks throughthe store to (5,4) close to metal shelf 1203. The new shelf 1203influences the RF signals received by the 3G cellular phone 1205 at(5,4). The 3G data communication signal data and WiFi signalcommunication data transmitted by 3G cellular phone 1205 to the server1206 provide RF fingerprint data for (5,4) that is inconsistent with thedata previously stored in the database. Upon determining that theinconsistency is due to a metal object, the server 1206 corrects theerror accordingly and stores the error information in the database orassociated therewith. A second person 1207 enters the hardware store1200 with an iPhone® 1208 and walks to (3,4). The iPhone® 1208 is incommunication with server 1206 is a similar fashion to the 3G cellularphone 1205 and transmits 3G data communication signal data and WiFisignal communication data to sever 1206 that is inconsistent with theexisting data for (3,4). Upon determining that the inconsistency is dueto a metal object, the server 1206 corrects the error accordingly andstores error data in the database or alternatively associated therewith.This process repeats N−1 times. An Nth person (not shown) enters thehardware store with an iPad® and walks close to metal shelf 1203. TheiPad® is in communication with server 1206 is a similar fashion to the3G cellular phone 1205 and iPhone® 1208, and transmits 3G datacommunication signal data and WiFi signal communication data to server1206 that is inconsistent with the existing data for the Nth person'slocation; however it is not inconsistent with data previouslytransmitted by the N−1 RF signal devices and therefore is consistentwith the error data. The data provided by the N RF signal devicesindicates that a new object is present. The “living database” is updatedbased on the error data and a metal shelf is added to the hardwarestore's map. Alternatively, when error data is indicative of somethingbut it is not resolved what that object is, mapping motion of customersabout the object helps in determining an appropriate update to mappingdata within the database. Optionally, the RF communication signals areBluetooth®, 4G or later cellular data signals, other RF signals, and areother than a GPS signal. Optionally the device is a cell phone, tablet,laptop, PDA, or other device comprising at least a receiver circuit forreceiving RF signals according to each of at least two standards.Typically, this is achieved using at least two RF signal receivercircuits.

According to an embodiment of the invention, a mapping platform is usedto map the interior of a building. FIG. 13 illustrates mapping platform1300 comprising stem 1301, crossbar 1302, handle 1304, and arm 1305.Crossbar 1302, handle 1304, and the first end of arm 1305 are coupled tothe stem, as shown. Mapping platform 1300 is also comprised of 2 wheels1306 a and 1306 b, each coupled to opposite ends of crossbar 1302, and 1wheel 1308 coupled to the second end of arm 1305, and mobile device1307, comprising RF communication circuitry. Arm 1305 is coupled to stem1301 via a apparatus such that the arm 1305 moves in 3 dimensions, x, y,and z. For example the apparatus is a ball and socket joint. Wheel 1308is coupled to the second end of arm 1305 such that the wheel rotates 360degrees. For example, the wheel is a castor wheel. Wheels 1306 a and1306 b are optically encoded, for example via transmissive opticalencoding, and are in communication with the mobile device 1307, forexample via Bluetooth®. Alternatively wheels 1306 a and 1306 b are incommunication with the mobile device 1307 via an RS-232 link.Alternatively wheels 1306 a and 1306 b are optically encoded viareflective optical encoding. A battery compartment 1309 disposed withinthe stem 1301 comprises batteries for powering the optically encodedwheels 1306 a and 1306 b. Optionally the batteries power otherelectronic devices coupled to the stem such as mobile device 1307. Thestem 1301 comprises a foldable joint 1310 such that the stem is foldableand made compact for carrying and storage.

According to, an embodiment of the invention, a mapping platform is usedto map the interior of a building. Referring to FIG. 14, holding thehandle of mapping platform 1402 a user 1401 pushes it through theinterior of hardware store 1400. Similar to a dead reckoning system, themapping platform's initial position is known. For example, the initialposition is determined by a GPS. As the user 1401 traverses the aislesof the hardware store 1400, a mobile device such as smartphone 1403,gathers RF fingerprint data for each location along the user's path. Inparallel, the optically encoded wheels transmit data associated with thedistance travelled to smartphone 1403. Two optically encoded wheels isuseful when determining distance travelled as they provide more datathan a single wheel resulting in increased accuracy of the measureddistance. Further, two wheels provides data in relation to turning andso forth. The smartphone 1403 transmits the RF fingerprint data and dataassociated with the distance travelled to a server to be processed, viaa wireless communication system, for example a Wi-Fi network.Alternately the wireless communication system is a cellular network. Arm1305 freely moves as the user's path changes direction or makes turnsproviding support and balance to the mapping platform 1402.

Optionally, the mapping platform comprises a compass coupled to the stemfor providing directional data to the server via the mobile device.Optionally, the mapping platform comprises an altimeter coupled to thestem for providing altitude data to the server via the mobile device.Altitude data is useful in determining location estimates as thedistance travelled will be corrected for uneven surfaces such as a ramp,Optionally three cameras are coupled to the mapping platform and arepositioned such that they capture the images in front of the mappingplatform and the images on the left and right of the mapping platform.The video data gathered is transmitted to the server for processing viathe mobile device. Video data gathered is useful in determining locationestimates as images sent from a customer can be compared with imagesstored in the server database to assist in determining locationestimates. Video data is correlated with RF fingerprint and locationdata to determine location estimates.

Alternatively, the mapping platform comprises a mobile communicationdevice comprising RF communication circuitry to communicate with theserver, for example via a Wi-Fi network, to transmit data collected bythe mapping platform data gathering devices for example, opticallyencoded wheels, compass, altimeter and video cameras. The mobilecommunication device also communicates with the data gathering devicesvia a wireless communication protocol, for example Bluetooth®.Alternatively, the mobile communication device also communicates withthe data gathering devices via a wired communication protocol, forexample an RS-232 link. Further alternatively the data collected by thedata gathering devices is stored in portable memory, to be extracted andprocessed at a later time.

Alternatively, the rear wheel in the embodiment of FIG. 13 comprisesencoders, for example similar to those on a trackpad or a mouse.Alternatively, the embodiment of FIG. 13 is implemented with includedwireless communication circuitry for transmitting data collectedthereby. Further alternatively, the wireless mapping platform collectsdata from a wireless device to which it is coupled and transmits all ofthe information sensed and collected to a server for storage in an RFfingerprint database. Yet further alternatively, the data is storedwithin the mapping platform for being transferred to a database at alater time.

Numerous other embodiments of the invention will be apparent to personsskilled in the art without departing from the scope of the invention asdefined in the appended claims.

What is claimed is:
 1. A method comprising: a. receiving at a firstelectronic device an RF signal comprising a first wireless signal and asecond wireless signal, the first wireless signal and the secondwireless signal other than solely a UPS signal; and b. based on both thefirst wireless signal and the second wireless signal, determining aregion of highest probability comprising an area of location estimatesfor the electronic device, the determined region of highest probabilityother than a region of highest probability determinable independentlywith each of the first RF signal and the second RF signal.
 2. A methodaccording to claim 1 wherein the region of highest probability isdetermined other than relying exclusively on triangulation.
 3. A methodaccording to claim 2 wherein the region of highest probability isdetermined other than relying on triangulation.
 4. A method according toclaim 1 wherein the region of highest probability includes at least somestatistical information relating to a probability of locations withinthe region.
 5. A method according to claim 1 wherein the region ofhighest probability is other than a regular shape.
 6. A method accordingto claim 5 wherein the region of highest probability is other than oneof a circle and a sphere.
 7. A method according to claim 1 wherein thefirst wireless signal and the second wireless signal are received atdifferent times.
 8. A method according to claim 7 wherein a velocityvalue estimation is determined and wherein the region of highestprobability is shaped based on a statistical likelihood in dependenceupon the velocity, the location estimates, and previous locationestimates.
 9. A method according to claim 7 wherein path data isdetermined and the region of highest probability is shaped based on astatistical likelihood dependent upon the path data, the locationestimates, and previous location estimates.
 10. A method according toclaim 1 comprising determining path data for a probable location of theelectronic device across different times for which wireless signals arereceived wherein determining the region of highest probability isfurther based on the path data.
 11. A method according to claim 10wherein the path data is based on regions of highest probabilitypreviously determined for the device.
 12. A method according to claim 10wherein path data is based on a statistical function relating to regionsof highest probability previously determined for the device.
 13. Amethod comprising: a. receiving at a first electronic device an RFsignal comprising a wireless signal according to a first standard and awireless signal according to a second standard, the first standard andthe second standard other than a GPS standard; b. determining a firstregion of highest probability estimate for an electronic device basedsolely on the wireless signal according to the first standard anddetermining a second region of highest probability estimate for theelectronic device based solely on the wireless signal according to thesecond standard; and c. determining a third region of highestprobability of the electronic device based on the first region ofhighest probability and the second region of highest probability.
 14. Amethod according to claim 13 wherein determining the third region ofhighest probability comprises: applying a known correlation between thefirst region of highest probability and the second region of highestprobability, the known correlation different for different regions ofhighest probability.
 15. A method according to claim 14 wherein theknown correlation is stored within a database and wherein the knowncorrelation comprises additional information, for relating locationestimates determinable based on signals according to each of the firstand second standards.
 16. A method comprising: a. receiving at a firstelectronic device a first wireless signal according to a first standardand receiving at the first electronic device a second wireless signalaccording to the first standard at a different time temporally proximateto the first wireless signal; b. determining a first region of highestprobability based on the first wireless signal and determining a secondregion of highest probability based on the second wireless signal; andc. determining the third region of highest probability of the electronicdevice based on the first region of highest probability and the secondregion of highest probability.
 17. A method comprising: a. receiving ata first electronic device a first wireless signal according to a firststandard and receiving at the first electronic device a second wirelesssignal according to the first standard at a different time temporallyproximate to the first wireless signal; b. receiving at the firstelectronic device a second first wireless signal according to a firststandard and receiving at the first electronic device a seconds secondwireless signal according to the first standard at a different timetemporally proximate to the first wireless signal and second wirelesssignal; c. determining a first region of highest probability based onthe first wireless signal and second wireless signal and determining asecond region of highest probability based on the second first wirelesssignal and second second wireless signal; and d. determining the thirdregion of highest probability of the electronic device based on thefirst region of highest probability and the second region of highestprobability.
 18. A method comprising: a. receiving at a first electronicdevice a first wireless signal according to a first standard andreceiving at the first electronic device a second wireless signalaccording to the first standard at a different time temporally proximateto the first wireless signal; b. receiving at the first electronicdevice a second first wireless signal according to the first standardand receiving at the first electronic device a second second wirelesssignal according to the first standard at a different time temporallyproximate to the first wireless signal and second wireless signal; c.determining a first region of highest probability based on the firstwireless signal, a second region of highest probability based on thesecond wireless signal, a second first region of highest probabilitybased on the second first wireless signal and a second second wirelesssignal based on the second second wireless signal; and d. determining athird region, of highest probability of the electronic device based onthe first region of highest probability, the second region of highestprobability, the second first region of highest probability, and thesecond second region of highest probability.
 19. A method comprising: a.receiving at a first electronic device a first wireless signal accordingto a first standard and receiving at the first electronic device asecond wireless signal according to the first standard; b. determining asecond measured time based on a difference between a second timeassociated with a second region of highest probability and a third timeassociated with a third region of highest probability; c. determining avelocity value based on the second measured time; and d. determininganother region of highest probability based on the first wirelesssignal, the second wireless signal, the second measured time, and thevelocity value.
 20. A method according to claim 19 comprisingdetermining a velocity function for a plurality of probable locations ofthe electronic device across different times for which wireless signalsare received wherein determining a third region of highest probabilityis based on a velocity value based on the velocity function.
 21. Amethod according to claim 20 wherein determining the velocity functioncomprises determining acceleration data.
 22. A method according to claim21 wherein determining the third region of highest probability isfurther based on the acceleration data.
 23. A method comprising: a.receiving at a first electronic device a first wireless signal and asecond wireless signal; b. determining using RF fingerprinting a firstregion of highest probability based on the first wireless signal; c.determining using RF fingerprinting a second region of highestprobability based on the second wireless signal; and d. determiningbased on the first and second regions of highest probability a thirdregion of highest probability for the electronic device.